In a time defined by high urbanisation rates and looming or existing crises, it is critical to understand how cities can turn into places of resilience and strength, rather than become centres of vulnerabilities. Cities face several challenges today, starting from the unpredictability of climate change. The COVID-19 pandemic showed how the magnitude and duration of disruptions are difficult to predict, challenging traditional risk-based management approaches to cope with crises. In this respect, resilience science has been taken up as it highlights the intricate, complex, and interdependent nature of urban systems. While a strict universal definition of resilience is lacking, it generally refers to the capacity to anticipate, withstand, adapt to and recover from shocks and stresses, such as natural disasters, economic downturns, public health crises, and social turmoil.

Very often, novel crises and emergencies tend to highlight and reveal long-existing, underlying problems. To increase resilience in an all-encompassing way, cities should focus on the deep-seated structural issues that hinder their capacity to adapt and thrive, such as inequality. In many urban areas, socioeconomic disparities are ingrained, with marginalised communities suffering most from crises. This policy brief is aimed at urban/local policymakers and stresses the need to consider inclusiveness in urban resilience. It discusses two (of the many) urban challenges that are periodically highlighted and exacerbated by new crises, such as energy poverty and service accessibility. The brief also offers some practical suggestions to develop an inclusive approach to a wider array of challenges derived from the programme Inclusive Climate Action Rotterdam.@en

This paper explores the perspectives of different urban actors regarding public participation in the context of the increasing incorporation of digital technologies and urban platforms. The study is based on three workshops with local governance actors, six semi-structured interviews with academics in the fields of public participation and digital technologies and a citizen survey with 260 respondents. The results provide multi-perspective insights into the challenges of participatory processes and are synthesized into three contributions: (i) guidelines for effective public participation, including factors that encourage or discourage citizen engagement; (ii) guidelines for designing participatory platforms, highlighting specific features that promote digital engagement (i.e. social media, gamification and user-friendly interfaces), and (iii) a typology of digital participation platforms to connect the diverse needs of actor groups with the various possibilities provided by new technologies. The guidelines provide concrete recommendations to support both urban practitioners and interface designers in designing participatory strategies and platforms, respectively. Recognizing that there is no-one-size-fits-all platform, the typology provides a framework for the assessment and further development of digital platforms for public participation.@en

As cities grow, the benefits of living in them are increasingly unequally distributed. USA cities, in particular, have experienced rapid suburbanization of poverty and decreased levels of access to jobs for transit-dependent and vulnerable communities. The public transit challenges in suburbs call for innovative forms of transit to turn the tide on urban inequality. On-demand microtransit, a novel type of shared mobility provides efficient, convenient and affordable transportation. Its potential for redressing inequity had yet to be investigated fully in a suburban setting. We presented a case study from the suburbs of Minneapolis-St. Paul in Minnesota, USA. We combined unique datasets of microtransit ridership from two public transit agencies, transit surveys, land use data, and expert interviews, to conduct spatial analysis, accessibility analysis, and equity impact assessments for these suburbs. We found that microtransit enables public transit agencies to reach a larger number of vulnerable riders than fixed-route transit, particularly for commuting and trips to/from commercial areas. Microtransit also provided a cheaper alternative to ride-hailing and a faster alternative to public transit and walking, without cannibalizing ridership from fixed-rout transit alternatives. Finally, microtransit redressed transportation inequities by alleviating access inequality, reaching vulnerable rider groups effectively, and creating travel opportunities that are less spatially concentrated than those provided by traditional, fixed-route public transit. This study provided a framework for further investigations into the impact of microtransit, including in urban core or rural settings, and highlighted the impact of microtransit in reducing access inequity in a suburban environment.

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Changes in policy over the last thirty years, particularly within advanced economies, have allowed for increased financialization, deregulation and globalisation of housing. What differentiates real-estate from other financial markets is that it possesses a salient socio-spatial geography. Housing inequalities are often framed as an outcome of macro-economic structural changes or as a product of local socio-spatial conditions, but the interactions between the two are less understood. To address this gap, we develop a descriptive methodology to connect the analysis of national housing policy trends in the Netherlands with local socio-spatial trajectories of neighbourhood change using nearly 20 years of historical data across a range of socio-spatial dimensions from the City of Rotterdam. Whilst nationally there has been an increasing policy preference for home ownership associated with a narrative of social upliftment, the spatial-temporal analysis reveals that the wealthiest neighbourhoods have benefitted significantly more from capital gains and increased rates of home ownership over time. Through descriptive analysis, the results highlight the role of divergent neighbourhood characteristics and path dependencies, suggesting that housing policies could benefit from the adoption of a more localised approach. Overall, the study sheds light on housing inequalities by integrating macro socio-economic factors with micro-level neighbourhood conditions.

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With developments in computational infrastructures, data science and AI have advanced, and in part replaced, several processes of engineering, design, and development in urban spaces. Former students and researchers from technical universities worldwide now work in all sectors of society and hold influential positions related to data science and AI. Yet, our education and research apparatus doesn’t fully intersect with the reality of the world where data and digitisation is not only a means to a better future but can also be wielded to maintain structures of inequality, oppression and harm. In curriculums that are focussed around data analytics and machine learning, education material is dominated by western perspectives and largely developed by able-bodied cis-gendered men, centring singular thinking in how we collect, clean, map, model, interpret and evaluate data, and share or cite evidence. Those who are represented get to shape futures for themselves (educated, urban, young adults), while the rest of the identities and issues are shifted to the margins of society. When colonial forms of education at scale are combined with nationally funded Artificial Intelligence programs of research, it legitimises data extraction and unequal forms of participation in decision, labour, and society, further perpetuating damages to vulnerable communities. To make space for alternate social realities, lived experiences, datasets, methodologies, map-building practices, and frameworks, we have developed a decolonising process for data science education. Our approach combines inserting non-western geographical knowledge with transdisciplinary, community participation, and intersectional and reflexive thinking to deliver an open, interactive, and co-created textbook for geographic data science education at engineering universities. We envision this process and exemplary textbook to provide entry points for local initiatives and needs to start thinking about their decolonising practices with respect to data and AI based education and research.@en

Governments often use price-based policies such as tax-subsidies and rebates to encourage households to shift to renewable energy sources like rooftop solar photovoltaics (PV). These policies, however, have primarily benefited high-income homeowners, leaving others behind. This paper proposes leveraging social networks’ influence on attitudes and perceptions to design more equitable solar PV adoption programs. Using data from Albany county (New York State, USA) we develop an Agent-based model, integrating a novel implementation of circles of influence into the theory of planned behavior. We test two policy categories (generic and targeted) under two network scenarios (integrated and segregated). Resulting solar PV adoption rates are evaluated using egalitarian, utilitarian and cost metrics to analyze policy impact on different income groups. Our findings indicate that network structure significantly influences adoption rates within income groups. Low-income groups in segregated networks can experience higher adoption driven by positive attitudes towards solar PV, while high-income groups in segregated networks may face poor policy performance despite higher affordability. Seeding policies and information dissemination through influential network members may not necessarily improve adoption rates, as trust can a more important role. The study underscores the importance of trusted information sources in influencing adoption decisions. The insights gained from this research can guide policy design for tailored interventions to improve access to renewable energy for all income groups.@en

Energy poverty is a pressing issue in the Netherlands, with the number of households struggling to cover their energy bills doubling to nearly one million in recent years. Current policies and subsidies have failed to address the needs of underprivileged social groups, leaving them vulnerable and unable to access support for dwelling renovations. This policy brief emphasises the importance of adopting a socio-spatial approach to tackle energy poverty and incorporate justice into renovation policies. By understanding the underlying factors that contribute to vulnerability and pinpointing their spatial distribution, targeted policies can be developed to meet the unique needs of vulnerable groups. The brief highlights the systemic challenges in Amsterdam Zuidoost, where low incomes, lack of trust, and financial constraints hinder renovation efforts. It stresses the urgency of adopting a spatial perspective, recognising the socio-spatial dimensions of vulnerability, and engaging local communities. Through inclusive and participatory processes, the brief aims to promote social equity, spatial justice, and sustainable solutions to combat energy poverty in Amsterdam Zuidoost.@en

Recent growth in residential solar PV systems in cities has largely contributed to decarbonizing our energy systems. However, the costs and benefits of this transition are not always equitably distributed. Socioeconomic variability has left disadvantaged social groups unable to access the benefits provided by solar PV systems and the stimulative policy measures associated to these systems. To enhance an equitable distribution of future solar PV resources, solar energy policy will need to be more considerate of its distributional impact. This research applies a socio-spatial perspective to understand and evaluate the differences in accessibility to solar PV systems for various social groups in the urban environment.@en

Driven by climate change and energy crises, an increasing number of households in the European Union are becoming vulnerable to energy poverty. However, current renovation programs fall short in effectively targeting and addressing the needs of vulnerable groups, particularly in underprivileged neighborhoods where low effectiveness rates and resident resistance to renovation measures persist. This exacerbates the risk of social and spatial inequity, calling for an urgent integration of justice considerations in European renovation policies. To address this challenge, this study proposes a novel case-study mixed methods (CS-MM) approach to include justice in renovation policies, considering the socio-spatial vulnerability to energy poverty. The case of Amsterdam Zuidoost is examined to achieve four main objectives: [1] identify systematic challenges in tackling energy poverty in underprivileged neighborhoods, [2] develop a vulnerability framework encompassing social, economic, energy, and building-related factors, [3] identify and localize energy vulnerable groups, and [4] tailor policy strategies in a multi-stakeholder environment based on the characteristics and needs of the identified vulnerable groups. The findings illustrate how the CS-MM approach can be applied to incorporate justice into renovation policies, informed by local insights on energy poverty. From a scientific perspective, this study contributes to the existing knowledge by providing insights into the identification of vulnerable groups, the inclusion of justice in renovation policies, and the deployment of a CS-MM approach to address socio-spatial vulnerability to energy poverty. From a societal standpoint, the findings empower local decision-makers to identify vulnerable groups and tailor policies accordingly.@en

This report (Deliverable 1.2) provides the DUST research project with a methodological
framework. It builds on the earlier methodology developed during preparation of the project
proposal, updating, expanding, and refining it in line with the development of the DUST
theoretical and framework (Deliverable 1.1) and the early insights from the research process. The purpose of this report is, first, to present the methodological approach of the DUST project to external audiences. Second, this deliverable aims to provide the DUST project team and the
stakeholders and experts involved with methodological guidance on each of the components of the projects and on the ways in which the different methods and research tasks interrelate to produce the expected results. This report is a ‘living document’, subject to updates as the project unfolds and research methods to be used in the specific tasks are further detailed and finetuned. The report outlines the overall methodological approach in the DUST project, including the workflow across its work packages. It also explains the strategy behind selecting the case study areas and briefly presents each of the regions studied. It then covers the research methods used in three phases of the project, namely, in the case study research, in the participatory experimentation following it, and in the exploration of affective communication with the communities engaged in the project. The report closes with a discussion on the synergies between the methods used and the measures taken to ensure validity of findings as well as an overview of the ways in which methodological innovation is delivered.@en

While social segregation is often assessed using static data concerning residential areas, the extent to which people with diverse background travel to the same destinations may offer an additional perspective on the extent of urban segregation. This study further contributes to the measurement of activity-based social segregation between multiple groups using public transport smart card data. In particular, social segregation is quantified using the ordinal information theory index to measure the income group mix at public transport journey destination zones. The method is applied to the public transport smart card data of Stockholm County, Sweden. Applying the index on 2017–2020 data sets for a selected week, shows significant differences between income groups’ segregation along the radial public transport corridors following the opening of a major rail project in the summer of 2017. The overall slight decrease in segregation over the years can be linked to declining segregation in the city center as a travel destination and its public transport hubs. Increasing zonal segregation is observed in suburban and rural zones with commuter train stations. This method helps to quantify social segregation, enriching the analysis of urban segregation and can aid in evaluating policies based on the dynamics of social life.

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Residential small-scale solar PV systems are expected to play an important role in reducing the current reliance on fossil fuels in the urban environment. However, not all households are equally capable of investing in solar PV technologies. Both the socioeconomic barriers in accessing renewable energy technology and the focus of solar energy policy on technology penetration rates alone has led to an oversight of equity concerns, disproportionately positioning households to have unequal access to participate in the renewable energy transition. This research aims to define and spatially assess the distribution of accessibility to residential solar PV systems across the urban environment, and evaluate how such access spatially intersects with rooftop solar potential. We observe significant patterns of spatial clustering regarding access to solar PV systems, aligning with the existing inequitable distribution of residential solar PV systems. Moreover, the majority of technical solar potential is located in areas where the capabilities of the population to access this potential are limited, indicating a significant amount of untapped potential in these areas. Analysing the intersection of accessibility to solar PV systems and rooftop solar potential will enhance understanding of where solar potential is more likely to be utilised and where households will need additional policy support to utilise this potential.@en

Identifying the diverse and often competing values of citizens, and resolving the consequent public value conflicts, are of significant importance for inclusive and integrated urban development. Scholars have highlighted that relational, value-laden urban space gives rise to many diverse conflicts that vary both spatially and temporally. Although notions of public value conflicts have been conceived in theory, there are few empirical studies that identify such values and their conflicts in urban space. Building on public value theory and using a case-study mixed-methods approach, this paper proposes a new approach to empirically investigate public value conflicts in urban space. Using unstructured participatory data of 4528 citizen contributions from a Public Participation Geographic Information Systems in Hamburg, Germany, natural language processing and spatial clustering techniques are used to identify areas of potential value conflicts. Four expert interviews assess and interpret these quantitative findings. By integrating quantitative assessments with the qualitative findings of the interviews, we identify 19 general public values and nine archetypical conflicts. On the basis of these results, this paper proposes a new conceptual model of ‘Public Value Spheres’ that extends the understanding of public value conflicts and helps to further account for the value-laden nature of urban space.@en

Over the last decade, solar energy has proven to be a key technology in transitioning to a sustainable energy system. However, current solar energy policies favour affluent households, limiting the participation of disadvantaged households in the energy transition. This leaves disadvantaged households even more vulnerable to increasing energy costs, as the recent unprecedented rise in energy prices has painfully demonstrated. To ensure that transition mechanisms are accessible to all households, solar energy policy needs to consider spatial justice. With this perspective, we go beyond technical analyses of solar energy potential and use a socio-spatial approach to evaluate the adoption of solar energy in The Hague. This policy brief is based on a research study that evaluated the transition to solar energy in the city of The Hague, The Netherlands, from a spatial justice perspective. Through a socio-spatial analysis at the postcode level, the research identified four distinct groups with varying levels of access to solar energy. The results show that these groups are not only strongly segregated across the city but also overlap with existing socio-spatial inequalities. The four levels of access to solar energy are then compared to current solar adoption rates and technical rooftop energy potential in the city. Results show that decreasing levels of access to solar energy align with decreasing adoption rates, revealing that current policies fail to provide equitable access to solar energy, leading to inequalities in adoption rates. Furthermore, the study quantifies how much of the technical potential available in The Hague is in areas where access to solar energy is limited, revealing a significant amount of untapped technical potential with the potential to address existing socio-spatial inequalities. Finally, two groups of interest and related leverage points for future policy interventions to address equity in the transition to solar energy in The Hague were identified.@en

The United Nations World Social Report (2020) reveals that more than two thirds of the world's population live in countries where urban inequalities have increased in the last three decades. While urban inequalities are traditionally characterized as an economic issue, scholars are increasingly applying methods from geospatial analysis to study them. In the context of these advancements, it remains unclear what underlying perspectives are guiding decisions to concentrate on certain aspects of urban inequalities, while potentially ignoring others. We address this gap by reviewing the literature centered on the geospatial analysis of urban inequalities and identify three predominant research lenses from accessibility, distribution, and policy and stakeholder perspectives. As a primary contribution of this article, we connect the perspectives with ideas drawn from complexity theory to develop an overarching socio-technical framework for how urban inequalities emerge over space and time. While traditional scientific frameworks seek to increase knowledge through causality, complexity science acknowledges the inherent challenges in defining, understanding and solving complex problems such as urban inequalities, which has profound implications for their representation, modeling and interpretation. We critically reflect on the framework through key relational themes and insights drawn from the literature and close with considerations for future research.@en

Bicycle networks are made up of different types of infrastructure for cars, bikes and mixed use, which has resulted in various definitions being used to describe them. However, it’s crucial to bring these definitions together to understand the structural differences among them and the impact of choices and investments in bike infrastructure. This study examines different definitions of bicycle networks in 47 cities, analysing scaling effects and various network metrics for four different definitions. Understanding structural characteristics of different bicycle networks definitions contributes to the body of knowledge necessary for design interventions by policymakers.@en

With technological advances and decreasing prices, solar energy is a key technology in the urban energy transition. However, the focus on increasing the overall installed capacity has overshadowed energy justice considerations, leading to inequalities in solar energy adoption. This paper adopts an equity perspective to analyse the transition to solar (photovoltaic) energy in the city of The Hague, The Netherlands. Access to solar energy is at the core of the research, encapsulating factors that influence the ability of a household to adopt solar energy. Through a socio-spatial analysis at the postcode level, we identify four distinct groups with varying levels of access to solar energy. Our results show that these groups are not only strongly segregated across the city but also overlap with existing socio-spatial inequalities. The four levels of access to solar energy are then compared to current solar adoption rates and technical rooftop energy potential in the city. Results show that decreasing levels of access to solar energy align with decreasing adoption rates, revealing that current policies fail to provide equitable access to solar energy leading to inequalities in adoption rates. Furthermore, we show that most of the technical potential available in The Hague is in areas where access to solar energy is limited, representing opportunities to exploit a significant amount of untapped technical potential while addressing existing socio-spatial inequalities. Here, we also identify two groups of interest and related leverage points for future policy interventions to address equity in the transition to solar energy in The Hague.

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Predictions on public transport ridership are beneficial as they allow for sufficient and cost-efficient deployment of vehicles. At an operational level, this relates to short-term predictions with lead times of less than an hour. Where conventional data sources on ridership, such as Automatic Fare Collection (AFC) data, may have longer lag times, in contrast, trip planner data is often available in (near) real-time. This paper analyzes how such data from a trip planner app can be utilized for short-term bus ridership predictions. This is combined with AFC data (in this case smart card data) to construct a ground-truth on actual ridership. The trip planner data is studied using correlation analysis to select informative variables, that are then used to develop 4 supervised machine learning models (linear, k-nearest neighbors, random forest, and gradient boosting decision tree). The best performing model relies on random forest regression and reduces the error by approximately half compared to a baseline model based on the weekly trend. We show that this model performance is maintained even for prediction lead times up to 30 minutes ahead, and for different periods of the day.@en

Cities consume almost 80 percent of world’s energy and account for 60 percent of all the emissions of carbon dioxide and significant amounts of other greenhouse gases (GHG). The ongoing rapid urbanization will further increase GHG emissions of cities. The quantification of the environmental impact generated in cities is an important step to curb the impact. In fact, quantifying the consumption activities taking place inside a city, if differentiated by socioeconomic and demographic groups, can provide important insights for sustainable-consumption policies. However, the lack of high-resolution data related to these activities makes it difficult to quantify urban GHG emissions (as well as other impacts). This paper presents a methodology that can quantify the carbon footprint of households in cities using consumption data from a national or European level, where the resource consumption is linked to socioeconomic attributes of a population. The methodology is applied to analyzing the environmental impact by household resource consumption in the city of The Hague in the Netherlands. The key insights reveal potential intervention areas regarding resource consumption categories and demographic groups that can be targeted to reduce GHG emissions due to consumption-driven activities in the city.@en